ACM ASIACCS 2021

Session Opening: Opening
Session Keynote-1: Keynote Session 1
Session 1A: ML and Security (I) Session 2A: Network and Web Security (I) Session 3A: Applied Cryptography (I)
Session 1B: Cyber-Physical Systems Session 2B: Hardware Security (I) Session 3B: ML and Security (II)
Session Poster-1: Social Event + Poster Session 1

Session Keynote-1

Keynote Session 1

Conference
9:30 AM — 10:30 AM HKT
Local
Jun 7 Mon, 8:30 PM — 9:30 PM CDT

Trustworthy Machine Learning: Past, Present, and Future

Somesh Jha (Lubar Professor, Computer Sciences Department, University of Wisconsin, Madison, USA)

5
Fueled by massive amounts of data, models produced by machine-learning (ML) algorithms, especially deep neural networks (DNNs), are being used in diverse domains where trustworthiness is a concern, including automotive systems, finance, healthcare, natural language processing, and malware detection. Of particular concern is the use of ML algorithms in cyber-physical systems (CPS), such as self-driving cars and aviation, where an adversary can cause serious consequences. Interest in this area of research has simply exploded. In this work, we will cover the state-of-the-art in trustworthy machine learning, and then cover some interesting future trends.
Session Chair

Man Ho Au

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